Machine Learning Engineer - Data Modeling

Description

• Working in a cross-functional agile team to deliver end-customer facing Machine Learning and Edge IoT applications through the complete development lifecycle from specification through to implementation, deployment, and support.
• Contributing to the evolution of the product architecture, adding significant new functionality, and improving the performance, scalability, and robustness of the IoT Cloud and Edge platform.
• Collaborating with a global, geographically dispersed team that is focused on delivering complementary layers of the infrastructure.
• Analyzing business user requests, estimate tasks throughout the project life cycle, design and document appropriate solutions, and design the business components and database objects required to implement the solution.
  

• Experience in statistical modeling, machine learning, data mining, unstructured data analytics, natural language processing.
• Experience with Deep learning libraries such as Tensorflow, Kera, OpenCV, PyTorch.
• Experience with Python developing Data Ingestion and Processing pipelines (ETL).
• Experience with Linux Ideally will have experience with Ubuntu 18.04 LTS.
• Experience in a variety of machine learning models (supervised, unsupervised, inference models from time-series data)
• Experience in processing, cleansing, and verifying the integrity of data used for Object recognition, Image Clustering, and Classification
• Experience in Selecting features, building high-quality prediction, recommendation systems, and optimizing classifiers using machine learning techniques
• Develop processes and tools to monitor and analyze model performance and data accuracy
• Good applied statistics skills, such as distributions, statistical testing, regression, etc.
• Good to have experience in IoT platform for providing IoT solutions using Azure IoT Edge and Azure IoT Hub service
• Good to have experience in Azure Cloud Platform PaaS & IaaS.
• Good to have experience with virtualization and containerization especially in technologies like Kubernetes, Docker
• Hands-on for doing required PoC for decision making.